Direct numerical simulation of bubble rising in turbulence

We describe the rising trajectory of bubbles in isotropic turbulence and quantify the slowdown of the mean rise velocity of bubbles with sizes within the inertial subrange. We perform direct numerical simulations of bubbles, for a wide range of turbulence intensity, bubble inertia and deformability, with systematic comparison with the corresponding quiescent case, with Reynolds number at the Taylor microscale from 38 to 77. Turbulent fluctuations randomise the rising trajectory and cause a reduction of the mean rise velocity $\tilde {w}_b$ compared with the rise velocity in quiescent flow $w_b$ . The decrease in mean rise velocity of bubbles $\tilde {w}_b/w_b$ is shown to be primarily a function of the ratio of the turbulence intensity and the buoyancy forces, described by the Froude number $Fr=u'/\sqrt {gd}$ , where $u'$ is the root-mean-square velocity fluctuations, $g$ is gravity and $d$ is the bubble diameter. The bubble inertia, characterised by the ratio of inertial to viscous forces (Galileo number), and the bubble deformability, characterised by the ratio of buoyancy forces to surface tension (Bond number), modulate the rise trajectory and velocity in quiescent fluid. The slowdown of these bubbles in the inertial subrange is not due to preferential sampling, as is the case with sub-Kolmogorov bubbles. Instead, it is caused by the nonlinear drag–velocity relationship, where velocity fluctuations lead to an increased average drag. For $Fr > 0.5$ , we confirm the scaling $\tilde {w}_b / w_b \propto 1 / Fr$ , as proposed previously by Ruth et al. ( J. Fluid Mech. , vol. 924, 2021, p. A2), over a wide range of bubble inertia and deformability.

Authors

Institutions

Publication Details

Journal
Journal of Fluid Mechanics
Published
2024-11-08
DOI
https://doi.org/10.1017/jfm.2024.763
Citations
7
Primary Topic
Particle Dynamics in Fluid Flows
Type
article
Field-Weighted Citation Impact
2.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Direct numerical simulation of bubble rising in turbulence

Luc Deike, Stéphane Perrard, Palas Kumar Farsoiya, Zehua Liu
7 citations
Journal of Fluid Mechanics
Particle Dynamics in Fluid Flows
2.35
article

Direct numerical simulation of bubble rising in turbulence

Luc Deike, Stéphane Perrard, Palas Kumar Farsoiya, Zehua Liu
article en
7 citations

Abstract

We describe the rising trajectory of bubbles in isotropic turbulence and quantify the slowdown of the mean rise velocity of bubbles with sizes within the inertial subrange. We perform direct numerical simulations of bubbles, for a wide range of turbulence intensity, bubble inertia and deformability, with systematic comparison with the corresponding quiescent case, with Reynolds number at the Taylor microscale from 38 to 77. Turbulent fluctuations randomise the rising trajectory and cause a reduction of the mean rise velocity $\tilde {w}_b$ compared with the rise velocity in quiescent flow $w_b$ . The decrease in mean rise velocity of bubbles $\tilde {w}_b/w_b$ is shown to be primarily a function of the ratio of the turbulence intensity and the buoyancy forces, described by the Froude number $Fr=u'/\sqrt {gd}$ , where $u'$ is the root-mean-square velocity fluctuations, $g$ is gravity and $d$ is the bubble diameter. The bubble inertia, characterised by the ratio of inertial to viscous forces (Galileo number), and the bubble deformability, characterised by the ratio of buoyancy forces to surface tension (Bond number), modulate the rise trajectory and velocity in quiescent fluid. The slowdown of these bubbles in the inertial subrange is not due to preferential sampling, as is the case with sub-Kolmogorov bubbles. Instead, it is caused by the nonlinear drag–velocity relationship, where velocity fluctuations lead to an increased average drag. For $Fr > 0.5$ , we confirm the scaling $\tilde {w}_b / w_b \propto 1 / Fr$ , as proposed previously by Ruth et al. ( J. Fluid Mech. , vol. 924, 2021, p. A2), over a wide range of bubble inertia and deformability.

Journal of Fluid MechanicsVol. 999
Centre National de la Recherche Scientifique (FR), Princeton University (US), Université Paris Cité (FR), Université Paris Sciences et Lettres (FR), Sorbonne Université (FR), Physique et Mécanique des Milieux Hétérogènes (FR), ESPCI Paris (FR)
National Science Foundation, University of Cambridge, Office of Advanced Cyberinfrastructure, Division of Chemical, Bioengineering, Environmental, and Transport Systems
Openalex Percentile: Top 12%
Particle Dynamics in Fluid Flows
2.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.